Systems and methods for delivering media content and improving diagnostic reading efficiency

ABSTRACT

Certain embodiments provide systems and methods for image delivery in a picture archiving and communication system. Certain embodiments provide a method for transferring image data via a delivery chain for display at a client workstation. The method includes creating a data list describing image data to be delivered to implement an imaging workflow. The method includes establishing a general loading plan to specify a recommended priority for delivery of the image data in the data list. The method includes generating a node loading plan for each node in the delivery chain based on the general loading plan. The method includes reconciling at least one of the general loading plan and the node loading plan. The method includes delivering the image data via the nodes of the delivery chain based on the general loading plan, the node loading plan for each node in the delivery chain, and the data list.

RELATED APPLICATIONS

The present application claims the benefit of priority to U.S.Provisional Application No. 60/989,378, filed on Nov. 20, 2007, entitled“Special Methodic for Delivering Media Content”, U.S. ProvisionalApplication No. 61/015,550, filed on Dec. 20, 2007, entitled“Improvement of Diagnostic Reading Efficiency Through Reduction of theLatency Time of Opening New Exam”, and U.S. Provisional Application No.60/989,375, filed on Nov. 20, 2007, entitled “Special Methodic for ImageHandling and Presentation”, each of which is herein incorporated byreference in its entirety.

FEDERALLY SPONSORED RESEARCH OR DEVELOPMENT

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MICROFICHE/COPYRIGHT REFERENCE

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BACKGROUND OF THE INVENTION

Healthcare environments, such as hospitals or clinics, includeinformation systems, such as hospital information systems (HIS),radiology information systems (RIS), clinical information systems (CIS),and cardiovascular information systems (CVIS), and storage systems, suchas picture archiving and communication systems (PACS), libraryinformation systems (LIS), and electronic medical records (EMR).Information stored may include patient medical histories, imaging data,test results, diagnosis information, management information, and/orscheduling information, for example. The information may be centrallystored or divided at a plurality of locations. Healthcare practitionersmay desire to access patient information or other information at variouspoints in a healthcare workflow. For example, during and/or aftersurgery, medical personnel may access patient information, such asimages of a patient's anatomy, that are stored in a medical informationsystem. Radiologist and/or other clinicians may review stored imagesand/or other information, for example.

Using a PACS and/or other workstation, a clinician, such as aradiologist, may perform a variety of activities, such as an imagereading, to facilitate a clinical workflow. A reading, such as aradiology or cardiology procedure reading, is a process of a healthcarepractitioner, such as a radiologist or a cardiologist, viewing digitalimages of a patient. The practitioner performs a diagnosis based on acontent of the diagnostic images and reports on results electronically(e.g., using dictation or otherwise) or on paper. The practitioner, suchas a radiologist or cardiologist, typically uses other tools to performdiagnosis. Some examples of other tools are prior and related prior(historical) exams and their results, laboratory exams (such as bloodwork), allergies, pathology results, medication, alerts, documentimages, and other tools. For example, a radiologist or cardiologisttypically looks into other systems such as laboratory information,electronic medical records, and healthcare information when readingexamination results.

PACS were initially used as an information infrastructure supportingstorage, distribution, and diagnostic reading of images acquired in thecourse of medical examinations. As PACS developed and became capable ofaccommodating vast volumes of information and its secure access, PACSbegan to expand into the information-oriented business and professionalareas of diagnostic and general healthcare enterprises. For variousreasons, including but not limited to a natural tendency of having oneinformation technology (IT) department, one server room, and one dataarchive/backup for all departments in healthcare enterprise, as well asone desktop workstation used for all business day activities of anyhealthcare professional, PACS is considered as a platform for growinginto a general IT solution for the majority of IT oriented services ofhealthcare enterprises.

Medical imaging devices now produce diagnostic images in a digitalrepresentation. The digital representation typically includes a twodimensional raster of the image equipped with a header includingcollateral information with respect to the image itself, patientdemographics, imaging technology, and other data used for properpresentation and diagnostic interpretation of the image. Often,diagnostic images are grouped in series each series representing imagesthat have some commonality and differ in one or more details. Forexample, images representing anatomical cross-sections of a human bodysubstantially normal to its vertical axis and differing by theirposition on that axis from top (head) to bottom (feet) are grouped inso-called axial series. A single medical exam, often referred as a“study” or an “exam” typically includes one or more series of images,such as images exposed before and after injection of contrast materialor images with different orientation or differing by any other relevantcircumstance(s) of imaging procedure. The digital images are forwardedto specialized archives equipped with proper means for safe storage,search, access, and distribution of the images and collateralinformation for successful diagnostic interpretation.

Diagnostic physicians that read a study digitally via access to a PACSfrom a local workstation currently suffer from a significant problemassociated with the speed of study opening and making studies availablefor review where the reading performance of some radiologists requiresopening up to 30 MRI studies an hour. Currently, a significant portionof a physician's time is spent just opening the study at the localworkstation. When a user is reading one study after another, a switchfrom a study just read to the next study to be read requires two mouseclicks (one to close the current study and one to open the next studyvia the physician worklist), introduces delay between those clicksnecessary for the refresh of the study list, and an additional delay forloading the next study.

Secondly, current mechanisms for loading a study do not allow fornegotiation between instances of a diagnostic viewer that are invoked atthe same time and share network bandwidth and processing capability onthe workstation trying to simultaneously downloading multiple studiesand respond to a user interface reading the study. This causes allstudies to load more slowly so that it takes proportionally longer forthe first study to become ready for reading. Such an approach isespecially detrimental for cases when the first study needs to bedownloaded as fast as possible, for example, when reading mammographystudies.

BRIEF SUMMARY OF THE INVENTION

Certain embodiments of the present invention provide systems and methodsfor image delivery in a picture archiving and communication system.

Certain embodiments provide a method for transferring image data via adelivery chain for display at a client workstation. The method includescreating a data list describing image data to be delivered to implementan imaging workflow. The method also includes establishing a generalloading plan to specify a recommended priority for delivery of the imagedata in the data list. The method further includes generating a nodeloading plan for each node in the delivery chain based on the generalloading plan. The method additionally includes reconciling at least oneof the general loading plan and the node loading plan. The method alsoincludes delivering the image data via the nodes of the delivery chainbased on the general loading plan, the node loading plan for each nodein the delivery chain, and the data list.

Certain embodiments provide a picture archiving and communication systemincluding a delivery chain including a plurality of nodes retrievingimage data from storage and transmitting the image data from a server toa workstation for display. The system also includes a processor andassociated memory including a data list and a general loading plan. Thedata list describes image data to be delivered to implement an imagingworkflow, and the general loading plan specifies a recommended priorityfor delivery of the image data in the data list. The processor providesa node loading plan to each node in the delivery chain based on thegeneral loading plan. The delivery chain operates with the data list,general loading plan, and each node loading plan to deliver requestedimage data via the delivery chain.

Certain embodiments provide a computer readable medium having a set ofinstructions for execution on a computing device. The set ofinstructions execute a method for transferring image data via a deliverychain for display at a client workstation. The method includes creatinga data list describing image data to be delivered to implement animaging workflow. The method also includes establishing a generalloading plan to specify a recommended priority for delivery of the imagedata in the data list. The method further includes generating a nodeloading plan for each node in the delivery chain based on the generalloading plan. The method additionally includes reconciling at least oneof the general loading plan and the node loading plan. The method alsoincludes delivering the image data via the nodes of the delivery chainbased on the general loading plan, the node loading plan for each nodein the delivery chain, and the data list.

BRIEF DESCRIPTION OF SEVERAL VIEWS OF THE DRAWINGS

FIG. 1 demonstrates a business and application diagram for PACSinformation system in accordance with an embodiment of the presentinvention.

FIG. 2 illustrates an embodiment of an information system deliveringapplication and business content in accordance with an embodiment of thepresent invention.

FIG. 3 illustrates a block diagram of an example clinical informationsystem that may be used to implement systems and methods describedherein.

FIG. 4 shows a block diagram of an example processor system that may beused to implement systems and methods described herein.

FIG. 5 illustrates a flow diagram for a method for transferring imagesfor display at a client workstation in accordance with an embodiment ofthe present invention.

The foregoing summary, as well as the following detailed description ofcertain embodiments of the present invention, will be better understoodwhen read in conjunction with the appended drawings. For the purpose ofillustrating the invention, certain embodiments are shown in thedrawings. It should be understood, however, that the present inventionis not limited to the arrangements and instrumentality shown in theattached drawings.

DETAILED DESCRIPTION OF THE INVENTION

Certain embodiments relate to reading and interpretation of diagnosticimaging studies, stored in their digital representation and searched,retrieved, and read using a PACS and/or other clinical system. Incertain embodiments, images can be stored on a centralized server whilereading is performed from one or more remote workstations connected tothe server via electronic information links. Remote viewing creates acertain latency between a request for image(s) for diagnostic readingand availability of the images on a local workstation for navigation andreading. Additionally, a single server often provides images for aplurality of workstations that can be connected through electronic linkswith different bandwidths. Differing bandwidth can create a problem withrespect to balanced splitting of the transmitting capacity of thecentral server between multiple clients. Further, diagnostic images canbe stored in one or more advanced compression formats allowing fortransmission of a lossy image representation that is continuouslyimproving until finally reaching a lossless, more exact representation.In addition, a number of images produced per standard medicalexamination continues to grow, reaching 2,500 to 4,000 images per onetypical computed tomography (CT) exam compared to 50 images per one exama decade ago.

Certain embodiments provide “smart” storage, transfer, usability andpresentation of diagnostic images to help alleviate certain problemspreviously found in digital picture archiving and communication systems(PACS) including but not limited to: (1) a load on an informationsystem, (2) a load on a network data transferring system, (3) heavyrequirements to image content storage volume; and (4) latency time forimage retrieval, image transmission, and image rendering on a diagnosticworkstation's display. Additionally, certain embodiments help facilitateimproved ergonomic screen layout, image manipulation, and imagepresentation for a diagnostic physician to provide more effective visualperception and diagnostic reading.

Prior to archiving, digital images are subjected to different types ofcompression for minimization of required capacity of storage andbandwidth of information links. One compression standard used in medicalimaging and other media content information systems is the JPEG2000standard, which allows decomposition of an image into multiplecompression layers, each layer representing a certain scale andresolution of the image. Transmitting a few of the most coarse layers ofthe image may be used to represent the general image but may compromisethe image quality with respect to finer image details. Although coarseimage representation is not sufficient for diagnostic visual perception,it still can be suitable for getting a first impression of anatomicalscene, navigating through a stack of images to identify a clinicallyrelevant anatomical area, and/or any other interactive preprocessing ofthe image or whole medical examination. Subsequent transmission anddecompression of additional layers enriches the image with fine detailsand, upon transmission of all layers, reproduce the image in its exactrepresentation.

In certain embodiments, rather than having only one preferredcompression scheme (e.g., jpeg, wavelet, layered, etc.), severalcompression schemes can be provided in a single system, includinguncompressed files. Certain embodiments provide a variety of techniquesfor handling thin slice data. For example, several thin slices and onethick slice can be combined. Certain embodiments utilize similarity ofneighboring images to take advantage of common values to compressimages. For example, information common to the slices and informationregarding differences between the slices are stored so that the imageslices can be compressed using an appropriate mechanism and can bedelivered to a workstation on request to enable fine grain reading ofdiagnostic images. Certain embodiments find applicability for both longterm and short term storage depending on a combination of price ofstorage, price of transfer, load on local and remote networks, price ofcompression (e.g., time), etc.

Certain embodiments provide systems and methods for transfer, improvedstorage, and improved presentation and perception of diagnostic imagesand other viewable media in order to help reduce system cost andcomplexity as well as physician waiting time and to help improveperformance and work quality for a physician (and/or other workstationoperator) to implement a workflow associated with reading, reviewing,and/or other utilization of the media.

Certain embodiments provide an information system for a healthcareenterprise including a PACS system for radiology and/or othersubspecialty system as demonstrated by the business and applicationdiagram in FIG. 1. The system 100 of FIG. 1 includes a clinicalapplication 110, such as a radiology, cardiology, ophthalmology,pathology, and/or application. The system 100 also includes a workflowdefinition 120 for each application 110. The workflow definitions 120communicate with a workflow engine 130. The workflow engine 130 is incommunication with a mirrored database 140, object definitions 60, andan object repository 170. The mirrored database 140 is in communicationwith a replicated storage 150. The object repository 170 includes datasuch as images, reports, documents, voice files, video clips, EKGinformation, etc.

An embodiment of an information system that delivers application andbusiness goals is presented in FIG. 2. The specific arrangement andcontents of the assemblies constituting this embodiment bears sufficientnovelty and constitute part of certain embodiments of the presentinvention. The information system 200 of FIG. 2 demonstrates servicesdivided among a service site 230, a customer site 210, and a clientcomputer 220. For example, a Dicom Server, HL7 Server, Web ServicesServer, Operations Server, database and other storage, an Object Server,and a Clinical Repository execute on a customer site 210. A Desk Shell,a Viewer, and a Desk Server execute on a client computer 220. A DicomController, Compiler, and the like execute on a service site 230. Thus,operational and data workflow may be divided, and only a small displayworkload is placed on the client computer 220, for example.

Certain embodiments provide an architecture and framework for a varietyof clinical applications. The framework can include front-end componentsincluding but not limited to a Graphical User Interface (GUI) and can bea thin client and/or thick client system to varying degree, which someor all applications and processing running on a client workstation, on aserver, and/or running partially on a client workstation and partiallyon a server, for example.

FIG. 3 shows a block diagram of an example clinical information system300 capable of implementing the example methods and systems describedherein. The example clinical information system 300 includes a hospitalinformation system (“HIS”) 302, a radiology information system (“RIS”)304, a picture archiving and communication system (“PACS”) 306, aninterface unit 308, a data center 310, and a plurality of workstations312. In the illustrated example, the HIS 302, the RIS 304, and the PACS306 are housed in a healthcare facility and locally archived. However,in other implementations, the HIS 302, the RIS 304, and/or the PACS 306may be housed one or more other suitable locations. In certainimplementations, one or more of the PACS 306, RIS 304, HIS 302, etc.,can be implemented remotely via a thin client and/or downloadablesoftware solution. Furthermore, one or more components of the clinicalinformation system 300 may be combined and/or implemented together. Forexample, the RIS 304 and/or the PACS 306 may be integrated with the HIS302; the PACS 306 may be integrated with the RIS 304; and/or the threeexample information systems 302, 304, and/or 306 may be integratedtogether. In other example implementations, the clinical informationsystem 300 includes a subset of the illustrated information systems 302,304, and/or 306. For example, the clinical information system 300 mayinclude only one or two of the HIS 302, the RIS 304, and/or the PACS306. Preferably, information (e.g., scheduling, test results,observations, diagnosis, etc.) is entered into the HIS 302, the RIS 304,and/or the PACS 306 by healthcare practitioners (e.g., radiologists,physicians, and/or technicians) before and/or after patient examination.

The HIS 302 stores medical information such as clinical reports, patientinformation, and/or administrative information received from, forexample, personnel at a hospital, clinic, and/or a physician's office.The RIS 304 stores information such as, for example, radiology reports,messages, warnings, alerts, patient scheduling information, patientdemographic data, patient tracking information, and/or physician andpatient status monitors. Additionally, the RIS 304 enables exam orderentry (e.g., ordering an x-ray of a patient) and image and film tracking(e.g., tracking identities of one or more people that have checked out afilm). In some examples, information in the RIS 304 is formattedaccording to the HL-7 (Health Level Seven) clinical communicationprotocol.

The PACS 306 stores medical images (e.g., x-rays, scans,three-dimensional renderings, etc.) as, for example, digital images in adatabase or registry. In some examples, the medical images are stored inthe PACS 306 using the Digital Imaging and Communications in Medicine(“DICOM”) format. Images are stored in the PACS 306 by healthcarepractitioners (e.g., imaging technicians, physicians, radiologists)after a medical imaging of a patient and/or are automaticallytransmitted from medical imaging devices to the PACS 306 for storage. Insome examples, the PACS 306 may also include a display device and/orviewing workstation to enable a healthcare practitioner to communicatewith the PACS 306.

The interface unit 308 includes a hospital information system interfaceconnection 314, a radiology information system interface connection 316,a PACS interface connection 318, and a data center interface connection320. The interface unit 308 facilities communication among the HIS 302,the RIS 304, the PACS 306, and/or the data center 310. The interfaceconnections 314, 316, 318, and 320 may be implemented by, for example, aWide Area Network (“WAN”) such as a private network or the Internet.Accordingly, the interface unit 308 includes one or more communicationcomponents such as, for example, an Ethernet device, an asynchronoustransfer mode (“ATM”) device, an 802.11 device, a DSL modem, a cablemodem, a cellular modem, etc. In turn, the data center 310 communicateswith the plurality of workstations 312, via a network 322, implementedat a plurality of locations (e.g., a hospital, clinic, doctor's office,other medical office, or terminal, etc.). The network 322 is implementedby, for example, the Internet, an intranet, a private network, a wiredor wireless Local Area Network, and/or a wired or wireless Wide AreaNetwork. In some examples, the interface unit 308 also includes a broker(e.g., a Mitra Imaging's PACS Broker) to allow medical information andmedical images to be transmitted together and stored together.

In operation, the interface unit 308 receives images, medical reports,administrative information, and/or other clinical information from theinformation systems 302, 304, 306 via the interface connections 314,316, 318. If necessary (e.g., when different formats of the receivedinformation are incompatible), the interface unit 308 translates orreformats (e.g., into Structured Query Language (“SQL”) or standardtext) the medical information, such as medical reports, to be properlystored at the data center 310. Preferably, the reformatted medicalinformation may be transmitted using a transmission protocol to enabledifferent medical information to share common identification elements,such as a patient name or social security number. Next, the interfaceunit 308 transmits the medical information to the data center 310 viathe data center interface connection 320. Finally, medical informationis stored in the data center 310 in, for example, the DICOM format,which enables medical images and corresponding medical information to betransmitted and stored together.

The medical information is later viewable and easily retrievable at oneor more of the workstations 312 (e.g., by their common identificationelement, such as a patient name or record number). The workstations 312may be any equipment (e.g., a personal computer) capable of executingsoftware that permits electronic data (e.g., medical reports) and/orelectronic medical images (e.g., x-rays, ultrasounds, MRI scans, etc.)to be acquired, stored, or transmitted for viewing and operation. Theworkstations 312 receive commands and/or other input from a user via,for example, a keyboard, mouse, track ball, microphone, etc. As shown inFIG. 3, the workstations 312 are connected to the network 322 and, thus,can communicate with each other, the data center 310, and/or any otherdevice coupled to the network 322. The workstations 312 are capable ofimplementing a user interface 324 to enable a healthcare practitioner tointeract with the clinical information system 300. For example, inresponse to a request from a physician, the user interface 324 presentsa patient medical history. Additionally, the user interface 324 includesone or more options related to the example methods and apparatusdescribed herein to organize such a medical history using classificationand severity parameters.

The example data center 310 of FIG. 3 is an archive to store informationsuch as, for example, images, data, medical reports, and/or, moregenerally, patient medical records. In addition, the data center 310 mayalso serve as a central conduit to information located at other sourcessuch as, for example, local archives, hospital informationsystems/radiology information systems (e.g., the HIS 302 and/or the RIS304), or medical imaging/storage systems (e.g., the PACS 306 and/orconnected imaging modalities). That is, the data center 310 may storelinks or indicators (e.g., identification numbers, patient names, orrecord numbers) to information. In the illustrated example, the datacenter 310 is managed by an application server provider (“ASP”) and islocated in a centralized location that may be accessed by a plurality ofsystems and facilities (e.g., hospitals, clinics, doctor's offices,other medical offices, and/or terminals). In some examples, the datacenter 310 may be spatially distant from the HIS 302, the RIS 304,and/or the PACS 306 (e.g., at General Electric® headquarters).

The example data center 310 of FIG. 3 includes a server 326, a database328, and a record organizer 330. The server 326 receives, processes, andconveys information to and from the components of the clinicalinformation system 300. The database 328 stores the medical informationdescribed herein and provides access thereto. The example recordorganizer 330 of FIG. 3 manages patient medical histories, for example.The record organizer 330 can also assist in procedure scheduling, forexample.

FIG. 4 is a block diagram of an example processor system 410 that may beused to implement systems and methods described herein. As shown in FIG.4, the processor system 410 includes a processor 412 that is coupled toan interconnection bus 414. The processor 412 may be any suitableprocessor, processing unit, or microprocessor, for example. Although notshown in FIG. 4, the system 410 may be a multi-processor system and,thus, may include one or more additional processors that are identicalor similar to the processor 412 and that are communicatively coupled tothe interconnection bus 414.

The processor 412 of FIG. 4 is coupled to a chipset 418, which includesa memory controller 420 and an input/output (“I/O”) controller 422. Asis well known, a chipset typically provides I/O and memory managementfunctions as well as a plurality of general purpose and/or specialpurpose registers, timers, etc. that are accessible or used by one ormore processors coupled to the chipset 418. The memory controller 420performs functions that enable the processor 412 (or processors if thereare multiple processors) to access a system memory 424 and a massstorage memory 425.

The system memory 424 may include any desired type of volatile and/ornon-volatile memory such as, for example, static random access memory(SRAM), dynamic random access memory (DRAM), flash memory, read-onlymemory (ROM), etc. The mass storage memory 425 may include any desiredtype of mass storage device including hard disk drives, optical drives,tape storage devices, etc.

The I/O controller 422 performs functions that enable the processor 412to communicate with peripheral input/output (“I/O”) devices 426 and 428and a network interface 430 via an I/O bus 432. The I/O devices 426 and428 may be any desired type of I/O device such as, for example, akeyboard, a video display or monitor, a mouse, etc. The networkinterface 430 may be, for example, an Ethernet device, an asynchronoustransfer mode (“ATM”) device, an 802.11 device, a DSL modem, a cablemodem, a cellular modem, etc. that enables the processor system 410 tocommunicate with another processor system.

While the memory controller 420 and the I/O controller 422 are depictedin FIG. 4 as separate blocks within the chipset 418, the functionsperformed by these blocks may be integrated within a singlesemiconductor circuit or may be implemented using two or more separateintegrated circuits.

According to certain embodiments considered as examples in the presentapplication, media files imported from a medical imaging device into aPACS are optionally subjected to a layered incremental compression.Certain media files are grouped in sequences called series, and certainseries are grouped into studies, where each study represents a total setof media associated with a single medical exam. Each such study can beoptionally attributed to a study type, where each study type isassociated with a certain protocol for study interpretation. Theprotocol can include but is not limited to an order and positions forseries display, configuration of a toolbar, annotation and measuringtools, and/or other data required for more efficient presentation ofdiagnostic images and rendering of a diagnosis. The set of tools andresources is referred to as a “study layout.”

For each study registered in the database, an algorithm (e.g., a uniquealgorithm) exists for creation of a list of respective series andindividual images included in the study and selection of a proper layoutfor study display. Upon getting a request for study display, the serverfirst generates comprehensive lists of media files to be used forreading the study and a related layout for study display. These listsare transferred to a client workstation and copies are kept on theserver. According to the generated list of media files and a chosenlayout for their presentation on the client workstation, a plan fortransferring and optional processing and/or decompression of the mediafiles is built and coordinated between client and server.

According to that plan, a first batch of media transfer includes aminimum amount of compression layers to deliver a coarse enoughrepresentation of the image(s) provided such that the coarserepresentation, while not suitable for diagnostic reading, is sufficientfor navigating between the images to review the whole study and thenfocus on images with high diagnostic value. Upon presentation of theimages on the diagnostic or other workstation, tools are offered to anoperator for implementation of a diagnostic workflow or other relevantworkflow. For example, tools can include but are not limited to:scrolling through the stack of images, adjusting brightness/contrast ofthe images, making measurements and annotations of the images, renderingsome other representation(s) such as three-dimensional (3D) or obliqueslicing, dictation and reporting tools, and/or other relevant tools.

In certain embodiments, an image transferring and decompression planprioritizes images such that media images that are currently visible ona client workstation have highest priority for transfer anddecompression of fine resolution layers. Thus, images that are currentlybeing reviewed to extract diagnostic features are more quicklytransferred and decompressed in their fine resolution representation, sothat each currently visible image more quickly reaches diagnosticquality, thus reducing perceived waiting time for a diagnostician.

In certain embodiments, an image transferring and decompression planprioritizes images such that those images that are currently not visibleon a workstation display but have a high probability of becoming visibledue to some interactive input of the user (e.g., user scrolling of theimage stack) also have sufficiently high priority for transfer anddecompression of their fine resolution layers. However, this prioritymay be lower than a priority for visible image layers, for example.According to one implementation of the transfer and decompression plan,those images reach the client workstation in their diagnostic qualitysoon after visible images thus reducing the latency time experienced bya diagnostician upon scrolling through the image stack or any otherscenario of re-focusing from one diagnostic image to the other.

In certain embodiments, an image transferring and decompression plan issensitive to user interaction upon implementation of a diagnosticreading workflow. For example, upon scrolling of any available imagestack, statuses of all images change, making some currently invisibleimages visible and making some currently visible images invisible. Thestatus changes are communicated to subsystems responsible for imagetransfer and decompression, triggering changes in implementation of theloading plan by changing priorities of transfer and decompression ofindividual images in coordination with changing image status.

While certain embodiments are described with respect to utilization oflayered compression and related diagnostics, other embodiments are notlimited to these approaches in other information systems. Certainembodiments can also apply to information and archiving systems used forstorage of uniform data or for different types of data and media.Certain embodiments can apply to information systems wherein one of thetargets of the information system is delivery of stored data to anapplication for interactive handling, subsequently referred to as“reading,” and implemented though a reading computer application.Reading can be implemented according to a plurality of differentscenarios or workflows further referred as “reading workflows.” Eachworkflow can involve a different nature of the data set available forreading application. The data set can include data of the same type orof multiple types. Different types of data for each workflow can be ofdifferent volume and can be used at different stages of the readingworkflow.

Since an information system cannot deliver an entire data set for areading workflow instantly, certain latency or “idle time” is introducedfor an operator implementing the reading workflow. Latency can be causedby, for example, limited bandwidth of communication lines, limited speedof data retrieval from storage media, limited speed for data search,and/or other technological or non-technological limitation.

Certain embodiments reduce latency in delivering images for a readingworkflow by providing an image loading plan. The plan includes adescription of reading workflows implemented and stored. The descriptioncan include, for example, a description of data types and data instancesfor successful running of the reading workflow. The description can alsoinclude a technical mechanism used for retrieval and delivery to areading application of particular data instances for each particularinstance of a reading workflow.

The loading plan can also include, for example, a description of whatdata should be available on a client workstation at any stage of thereading workflow in accordance with its normal implementation or inreaction to interactive actions of the operator. The description canspecify data that should be delivered to the workstation forimplementation of the next stages of the reading workflow upon mostprobable interactive interventions of the operator, for example.

Delivery engines and other hardware/software can be arranged in adelivery chain to provide sequential delivery of data or its usablepieces through a chain of information subsystems from original datastorage to the client workstation in accordance with the loading plan.

The loading plan and delivery chain can identify that the readingworkflow has proceeded to a next step due to a progression of eventsand/or in response to human interaction. Missing data pieces for a nextstep of the reading workflow are identified, and missing datainformation is broadcast to all or selected delivery components. Forexample, delivery hardware and/or software impacted by the missing dataare notified about the missing information.

Loading plans governing sequential actions of delivery components can bereconciled in accordance with proceeding to a next stage of the readingworkflow and accounting for the missing data. Reconciliations of theloading plans of different delivery elements are coordinated to helpreduce or eliminate data traffic congestions through the delivery chain.

Load on components of the delivery chain(s) that serve several datadestinations can be balanced through partitioning between thedestinations so that data traffic to all destinations of the same datadelivery component is in proportion to a bandwidth of a link between thedelivery components and in proportion to a capacity of each datadestination to receive and process incoming data and/or data pieces.

In certain embodiments, utilization of lossless, lossy, and/or layeredcompression can be utilized so that the loading plan(s) can incorporateloading of partial (e.g., lossy) data on certain stages of a readingworkflow, with optional increasing of data quality to less lossy or evenfully lossless by loading of extra compression layers of the same data.

Thus, certain embodiments provide a PACS configured for importing,storage, access, distribution, and/or interpretation of radiologicalexams presented as a plurality of digital images and other diagnosticdata including but not limited to textual, visual, audio, graphical,and/or other types of data. The PACS can utilize a single data typeand/or a combination of different data types with different scenariosfor interpretation, management, and/or other functional purposesreferred to as workflows, for example. The PACS includes deliveryhardware for retrieval of data from physical storage, optionalprocessing of the data, and transferring of the data to a clientapplication. The client application can reside, for example, on the samehardware installation that includes an informational server and physicaldata storage or on a remote computer connected to the information systemthrough a LAN, WAN, or Internet connection, for example.

The PACS includes one or more delivery engines or dedicated softwareobjects/agents controlling delivery hardware components for delivery ofdigital data from storage to an end user. Delivery includes but is notlimited to retrieval of the data from its original physical storage,optional transmission of the data through a LAN, WAN, Internet, or otherconnection, and optional compression/decompression or otherwiseorganized data processing on its way from original physical storage tothe end-user client application, for example.

Delivery agents represented by delivery hardware and delivery enginescan be optionally arranged in a chain of delivery nodes. Data used bysome of delivery nodes for transfer or processing is provided to thedelivery nodes by another delivery node called a source delivery node.Data processed or transferred by some other delivery node is used by asubsequent delivery node referred to as a sink delivery node for furthertransfer and/or processing, for example.

The PACS includes hardware and/or software for creation, storage, and/ormodification of data lists including a description of a plurality ofdata types and a plurality of data objects that should be delivered to aworkstation or server for implementation of a workflow. Data lists areretrievable in response to launching a workflow on a workstation orserver. Data lists are implemented as explicit lists and/or graphs,recursive lists and/or graphs, on-the fly logical algorithms, and/orother representation, for example.

The PACS establishes one or more loading plans specifying a preferredpriority or order for delivery of different objects referred to in adata list to a client/display workstation and/or server in accordancewith an implementation of a workflow and/or in accordance with mostprobable deviations from a workflow implementation resulting from humaninteractions and/or other factor(s).

The PACS generates a node/engine loading plan for each deliverynode/engine based on the general loading plan. The loading plan and/orplans serve as an operational algorithm for the delivery node/engine.

The PACS includes software and/or hardware for reconsideration andreconciliation of a general loading plan and node/engine loading plansfor relevant delivery nodes/engines in response to proceeding to a nextstep of the workflow and/or changing of the workflow implementation, forexample.

The PACS can coordinate loading plans for a plurality of deliverynodes/engines along a delivery chain to reduce data congestion along thedelivery chain.

The PACS can synchronize reconciliation of node loading plans betweendelivery nodes serving a workflow.

The PACS includes software and/or hardware for changing a priority,order, and/or speed of data retrieval, transfer, and/or processing bydelivery nodes/engines in response to an updated node loading plan.

In certain embodiments, the PACS includes several delivery engines/nodesthat concurrently deliver data for several independent workflows. Thedelivering engine/nodes share common system resource(s) including butnot limited to network bandwidth, storage access, CPU, etc. Sharedresource(s) impose productivity limitations for concurrent operation ofthe delivery engines/nodes (referred to as parallel deliveryengines/nodes). The PACS also includes hardware and/or software forbalancing a load of parallel delivery engines/nodes for fair andeffective distribution of shared system resources between severalindependent workflows.

In certain embodiments, the. PACS includes several deliveryengines/nodes arranged in a plurality of delivery chains thatconcurrently deliver data for a plurality of independent workflows. Thedelivering engines/nodes share common system resource(s) including butnot limited to network bandwidth, storage access, CPU, etc. The sharedresource(s) impose productivity limitations for concurrent operation ofthe delivery engines (called parallel delivery engines/nodes). The PACSincludes hardware and/or software that provide load balancing ofparallel delivery engines/nodes for distribution of shared systemresource(s) between several independent workflows and in considerationof capacity and/or traffic of adjacent source and sink deliveryengines/nodes.

In certain embodiments, the PACS stores and/or generates at leastselected types of data in compressed form and utilizes loading plan(s)having special provisions for delivery of data compressed to a differentdegree of lossy compression for initialization of a workflow and/or ondifferent stages of workflow implementation.

In certain embodiments, the PACS includes a general purpose compact ordistributed information system designed and used for import, storage,and/or distribution of a uniform data type or data of different naturesthat includes usage data of a uniform type or a combination of data ofdifferent natures within different scenarios (e.g., workflows) ofinterpretation, management, and/or other functional purpose. The PACSincludes delivery hardware from retrieval of data from physical storage,optional processing of the data, and transferring of the data to aclient application, provided that the client application can resideeither on the same hardware installation that includes an informationalserver and physical data storage or on remote computer connected to theinformation system through a LAN, WAN, Internet, and/or other dataconnection. The PACS includes one or more delivery engines—dedicatedsoftware objects/agents controlling delivery hardware component(s) fordelivery of digital data from its original storage to an end user.Delivery includes but is not limited to retrieval of the data from itsoriginal physical storage, optional transmission of the data throughLAN, WAN, Internet, and/or other connection, and optionalcompression/decompression or otherwise organized data processing as thedata is on its way from original physical storage to the end-userapplication. Delivery agents represented by delivery hardware anddelivery engines may be optionally arranged in a chain of delivery nodessuch that data used by some delivery node(s) for transfer or processingis provided to the delivery node(s) by another delivery node called asource delivery node, while data processed or transferred by anotherdelivery node is used by a subsequent delivery node called a sinkdelivery node for further transfer and/or processing. The PACS includesmeans for creation, storage, and modification of the data lists—acomprehensive description of plurality of data types and plurality ofdata objects that should be delivered to respective workstation orserver for successful implementation of the workflow. The data lists areretrieval in response to launching any workflow on any workstation orserver implemented either as explicit lists and/or graphs, recursivelists and/or graphs, on the fly logical algorithms, or other means mostproper for any preferred embodiment of the invention. The PACS canestablish one or more loading plans representing a preferred priority ororder for the delivery of different objects referred to in the data listto respective workstation(s) and/or server(s) in accordance with animplementation of a workflow and/or in accordance with one or more mostprobable deviations from a normal workflow implementation resulting fromhuman interactions and/or any other factors. The PACS generates anode/engine loading plan for each delivery node/engine based on thegeneral loading plan. The loading plan and/or plans serve as anoperational algorithm for a delivery node/engine. The PACS canfacilitate reconsideration and reconciliation of the general loadingplan and/or node/engine loading plans for all relevant deliverynodes/engines in response to a next step in the workflow and/or changingof the workflow implementation. The PACS can coordinate the loadingplans for a plurality of delivery nodes/engines along the delivery chainto reduce data congestion along delivery chain. The PACS can synchronizereconciliation of the node loading plans between all delivery nodesserving a workflow. The PACS can adjust a priority, order, and/or speedof data retrieval, transfer, and/or processing by the deliverynodes/engines in response to an updated node loading plan.

In certain embodiments, the PACS includes several delivery engines/nodesthat concurrently deliver data for several independent workflows. Thedelivery engine/nodes share common system resource(s) including but notlimited to network bandwidth, storage access, CPU, etc. The sharedresource(s) impose a productivity limitation for concurrent operation ofthe delivery engines/nodes (referred to as parallel deliveryengines/nodes). The PACS can also balance a load of parallel deliveryengines/nodes to distribute shared system resources between severalindependent workflows.

In certain embodiments, the PACS includes several delivery engines/nodesthat concurrently deliver data for a plurality of independent workflowsarranged in a plurality of delivery chains. The delivery engines/nodesshare common system resource(s) including but not limited to networkbandwidth, storage access, CPU, etc. The shared resource(s) impose aproductivity limitation for concurrent operation of the delivery engines(referred to as parallel delivery engines/nodes). The PACS can also helpprovide an optimum load balance of parallel delivery engines/nodes tohelp distribution of shared system resources between several independentworkflows and in consideration of capacity and/or traffic of adjacentsource and sink delivery engines/nodes, for example.

In certain embodiments, the PACS stores and/or generates at leastselected types of data in compressed form and utilizes loading plan(s)having special provisions for delivery of the data compressed todifferent degree(s) of lossy compression for initialization of aworkflow and/or on different stages of workflow implementation.

Using the PACS, image data can be processed, transferred, and displayedin a variety of ways. A few exemplary scenarios are given below forpurposes of illustration and are not exclusive.

According to one embodiment, diagnostic images imported by a PACS do notundergo immediate compression if a bandwidth of one or more informationlinks used for delivery of the images to the workstation(s) is wideenough to facilitate prompt downloading of images to the localworkstations. The “wide enough” criteria can be established in aplurality of ways including but not limited to: (1) determined by adirect assessment of the actual bandwidth of the data links, (2) setmanually upon configuration of the system, (c) a combination of above,etc. According to this embodiment, diagnostic images stored in thesystem can be further optionally subjected to “aging” compression toreduce a volume of long term storage to either lossless or lossyquality. An exact compression ratio formula can be based on acombination of factors that can be assessed individually for each imageor collectively for a plurality of images. Factors include but are notlimited to a combination of: diagnostic modality, nature of exam, timeelapsed from exam itself and/or from last access to the image(s),institution and/or governmental regulations, etc. The “agingcompression” can be optionally scheduled for “low CPU usage hours” andtriggered by a combination of factors, the exact formula based on butnot limited to combination of: age of the images, time elapsed sincelast access to images, diagnostic modality and/or nature of the exam,regulations and preferences of institutions, societies and individuals,and/or other factors.

Compression algorithms often attempt to squeeze the volume of the imagedata as close as possible to a minimum. With multi-slice CT, forexample, image data occupies gigabytes because the entry level andimages reside on a computer but must be uncompressed, a process whichtakes time, especially for images processed and compressed by a thirdparty system. Images can be prioritized such that an active imagereceives priority for loading and the next image behind the active imagereceives priority as well. If a certain compression method fails toprovide sufficient throughput and/or response time, network shortcomingsmay be addressed instead. For example, a three dimensional viewer mayneed all volume data decompressed rather than using partial data.Therefore, in certain cases, images may not be compressed at all.

Thus, certain embodiments provide adaptive compression to determinewhether to compress or provide image data uncompressed or to provide acombination of compressed and uncompressed image data. In certainembodiments, a PACS server may store two copies, one compressed and onenon-compressed, and choose which one to transfer. May choose, forexample, if within hospital use non-compressed.

As an example, if a physician is working from home, compression of imagedata may be appropriate, but the user may not need adaptive compressionwith prioritization. In certain embodiments, the system can adjust thecompression method dynamically as data is being transferred. Forexample, a transfer may begin with compressed data and then determinethat all the images should be transferred for viewing rather a sequenceof one by one. However, available processing power may be lower thanavailable bandwidth on the transmission line, so the bottleneck is dueto compression. As a result, the remainder of transferred images can betransferred using a decompressed representation. Transmission status canbe reviewed again and transmission/compression format can be changedagain. Thus, aging compression involves evaluating image datatransmission and compression and adjusting compression and/or imageresolution based on transmission status, for example.

According to another embodiment, similar to the embodiment describedabove, images are delivered to a viewing workstation either in acompressed or in an original (non-compressed) format. A decisionregarding the delivery format is made by a formula based on acombination of certain factors including but not limited to: a bandwidthof an information link between server and workstation, a type ofinformation link (e.g., local area network (LAN), wide area network(WAN), Internet, virtual private network (VPN), other), processing powerof the workstation, institution policy, individual preferences, etc. Oneor more of the selected factors can be (a) set manually uponconfiguration of the system and/or setting policy and/or preferences;(b) assessed automatically upon system functioning; (c) by combinationof the above; and/or (d) by other suitable method. Selective deliverycan be facilitated by keeping multiple copies of the same data in allinvolved formats or by “on-demand” preparation of a particular formatfrom one or more storage format(s) by a processing engine.

According to another embodiment, images and data used for rendering afirst screen on a display workstation and initiating a correspondinginteractive or automated workflow are delivered in a special “start up”format. The format is one effective for reducing latency time inawaiting the first visual screen and/or other resources for initiationof the workstation's workflow. The start-up format is defined by aformula based on a combination of certain factors including but notlimited to: bandwidth of an information link between server andworkstation, a type of link (e.g., LAN, WAN, Internet, VPN, etc.),processing power of the workstation, institution policy, individualpreferences, etc. One or more of the selected factor(s) can be (a) setmanually upon configuration of the system and/or setting policy and/orpreferences; (b) assessed automatically upon system functioning; (c) bya combination of the above; and/or (d) by other suitable method.

The “start-up” data format can be predetermined and securely stored onthe server, or created on-demand by conversion from a storage format bya processing engine. Subsequent data delivered to the workstation afterinitiation start-up screen and workflow can be delivered by otherloading format(s) and/or other loading plan(s) including but not limitedto those disclosed in other embodiments.

The special start up or initial format can be implemented in a varietyof ways. For example, the special format can be an overview screenshotof certain images but not a single individual image. This first contentfor the screen can be prepared in advance. An image study can bereviewed to create a metadata file describing the whole study but notbuilding the study. Building the study can be performed by retrievingimages with the same study number from an image database, for example,and delivered to a client workstation in digested form while thepre-form first content (e.g., a static first view) is being displayed toa reviewing physician at the client workstation. For example, apre-generated first view typical for that workstation, such as a staticoverview image, can be provided to allow the physician to spend a fewseconds looking rather than being idle and waiting for image delivery.

According to another embodiment, an information system imports a seriesof images that represent substantially parallel cross-sections of apatient anatomy and sweep some anatomical volume with high density ofsubstantially adjacent image. Thus, the series of images provides highspatial resolution at least in a direction normal to the planes ofcross-sections. According to this embodiment, the image series can besubjected to “aging consolidation” by grouping an initial series ofimages into a plurality of spatially confined and successively adjacentgroups of images and consolidating a plurality of consecutive imagesbelonging to a same spatially confined group into one image or anotherplurality of images with reduced spatial resolution while substantiallyrepresenting an anatomical slab covered by a respective group ofinitially non-consolidated of images.

Image slice consolidation can be achieved by a variety of methodsincluding but not limited to: combining respective pixels of neighboringimages into one pixel; combining a plurality of neighboring pixels ofthe same image into one pixel; and/or combining respective groups ofneighboring pixels on neighboring slices into one pixel, for example.

As discussed above, combining respective pixels of neighboring imagesinto one pixel can be achieved by a variety of methods including but notlimited to: mean value, median value, maximum value, minimum value, etc.Combining a group of neighboring pixels of the same image into one pixelcan be achieved by a variety of methods including but not limited to:mean value, median value, maximum value, minimum value, etc. Combiningrespective groups of neighboring pixels on neighboring slices into onepixel can be achieved by a variety of methods including but not limitedto: mean value, median value, maximum value, minimum value, etc.

The method used and consolidation formula are based on the combinationof factors including but not limited to: diagnostic modality, initialspatial resolution, nature of exam, time elapsed from exam and/or fromlast access to the data, institution and/or governmental regulations,etc. Consolidation can be scheduled for “low CPU usage hours” andtriggered by a scheduling formula based on a combination of factorsincluding but not limited to: age of the images; time elapsed since lastaccess to images, diagnostic modality and/or nature of the exam,regulations and preferences of institutions, societies and individuals,etc.

CT scanners can produce slices with a thickness of less than 1 mm withhigh resolution. Rendering three dimensional images involves slices withhigh resolution. Sometimes high resolution is used when looking for tinydetails (e.g., vessels, plaque on vessel walls, etc.) in images. Tostore these high resolution slices is expensive as is transferring thembecause a wide bandwidth network is used. Therefore, dedicatedworkstations are often configured to use high resolution data, whichthey then send to a PACS workstation as consolidated data (e.g.,averaging image data across four slices of 0.7 mm into one slice of 3mm) so that the PACS workstation displays images of inferior quality todedicated workstations. However, the PACS can store patient historyinformation and includes diagnostic tools, etc.

Rather than forcing a physician to physically move to a dedicatedviewing workstation for better presentation but no additional patientinformation, which often involves moving from a dark room to a lightroom and back to a dark room (thus interfering with a physician'svision), certain embodiments provide launching of all such content froma PACS workstation. If a server or other system sends lower resolutiondata to a PACS workstation and then needs to send high resolution data,two sets of data (e.g., one low resolution and one high resolution) canbe sent.

According to another embodiment, the previous embodiment is modifiedsuch that in addition to producing a set of consolidated lowerresolution images, a difference between initial data and consolidateddata is calculated and stored in the system in a form targeted forsubstantial preserving of high resolution data for its optional usagewhen diagnostic quality of low resolution consolidated images is notsufficient. Calculating and storing the difference can help improvestorage performance and/or reduce storage cost, for example. Storage ofthe difference between high resolution and low resolution data caninclude but is not limited to following: the difference is converted tocompressed lossless or lossy format and stored together withconsolidated data; the difference is converted to another reducedresolution format stored together with consolidated data; the differenceis converted to an appropriate format including but not limited tocompressed and/or reduced resolution and/or original format, but storedin some storage other than the storage used for consolidated data withlower price per megabyte or for any other practical reason, for example.

Thus, a physician or other user of the system can access aged imageswith reduced spatial resolution, while having an ability to access thefull resolution images in a substantially representative appearance. Thesubstantially representative appearance of the full resolution data canbe reconstructed in advance or on-demand by adding to each consolidatedimage the difference between original image and consolidated one. Thedifference can be pre-calculated as part of the aging consolidation, forexample.

As an example, a reference frame can be stored along with a differencebetween each reference frame and surrounding intermediate frames. Asanother example, rather than using every tenth frame as representativeimage data, an average of each consecutive ten frames is determined togenerate a consolidated representation of the anatomical value. Thus, athick image slice can be created that has image data values as if theslice was generated with an old modality at thickness of, for example, 3mm rather than 0.7 mm. The thicker slice may be good for comparison butnot for sophisticated volume rendered or analysis applications, forexample.

For the remainder of the image data, there are many economical ways tostore that difference data. For example, a lossy compression can be usedto make compromises on low level details but maintain high leveldifference information between images. Difference data can be maintainedon a remote storage with high latency access but low cost, for example.The difference data can have its own life cycle and plan. For example,image difference data may be kept whole on an image archive and, after ayear, be subject to lossy compression for further storage. After anotheryear, the compressed data is subject to another lossy compression, and,after five years, the archived difference data is deleted, for example.

Additionally, certain embodiments help to reduce time spent opening astudy from a PACS to a local workstation through automatic, configurablepre-loading strategies to automatically pre-load the next study intendedfor reading to the client workstation and performing data preprocessingbefore the user starts a diagnostic reading of that study, so thatdelays associated with study loading are reduced or minimized.Furthermore, certain embodiments provide for negotiation betweendiagnostic viewer instances invoked at the same time and sharing networkbandwidth and processing power on the workstation trying tosimultaneously download multiple studies and respond to user interfacequeries reading the study.

As an example, certain embodiments attempt to maintain a time to displayof a first image the same regardless of the study size. The system canidentify which images can be delivered first to render an image spacefor initial review by a radiologist. When images are to be derived fromtwo image series (e.g., a PET CT combined from an image providingmetabolic information and an image providing anatomic information), thesmaller data set is loaded first. If there are many images, a data setcan be concatenated, and loading can start from a reduced data set thatis sufficient to be shown to radiologists for studying orientation andnavigation between images. While he or she navigates, image downloadingcontinues. A reduced or sparse representation can be created in advance,for example. For example, a volume of data in PET images is much lowerthan in CT images, but PET images include functional information for aphysician to begin his or her analysis. Therefore, some subset that issubstantially smaller than the other data can be loaded first.Alternatively or in addition, a subset can be created that is somesampling (e.g., every 3^(rd) image, every 5^(th) image) of the largerset. Thus, a representative subset of data is created, optionally in acoarser resolution, and also optionally save to the workstation somemetadata regarding this reduced subset of images. For example, a seriesincludes one axial image, one lateral image, one image with contrast,one image without contrast. The first series has a certain number ofimages, and the first image has a certain orientation, for example. If auser wants to open the first image, the application is directed to acertain location in memory. Thus, time is saved not only in transferringthe images but also in creating the associated metadata for the images.An application can parse not only the image data but also the metadatafor the image.

To provide better performance for mammography integration in particular,certain embodiments provide a new mode of PACS operation referred toherein as AutoFetch. However, use of the name AutoFetch should not beconstrued to limit embodiments to pre-fetching data from a remote serverto a local workstation but is instead used in a broad sense ofpre-fetching, pre-arranging, and pre-processing of data according to apreferred scenario of diagnostic reading by a physician. Steps areimplemented in the background so that a latency time between finalizingreading of a previous study and starting a next study reading is reducedor minimized, for example.

In certain embodiments, a user is able to turn on and off the AutoFetchfunctionality which pre-loads one or more studies according the order ofthe studies on a worklist. A user can specify certain parameters ofpre-loading, such as a “stay-ahead factor.” AutoFetch can negotiate aloading order between multiple instances of a diagnostic viewer.AutoFetch can automatically launch data pre-processing and/or datagrooming engines if involved in a mode of diagnostic reading specifiedfor the study. Switching from reading the current study to the nextstudy preloaded by AutoFetch can be done with one mouse click andreduced delay between closing a study and opening the next study, forexample.

An efficient reading sequence workflow involves a user marking aworklist as a “reading sequence.” More than one worklist for a user canhave such a designation. Opening a study from such a worklist initiatesthe reading sequence. Only one sequence can be active at a time. Openinga study from another worklist while the reading sequence is active willnot initiate another sequence.

When a study from the worklist with an active reading sequence opens,the next study on the worklist, unless it is already locked from viewingby a different user, begins downloading in the background (e.g.,transparently to the user). The downloading process is given a lowerpriority so as not to affect performance of reading of the open study.The next study can also be locked from view at this point. The nextstudy is defined as the first study on the worklist (e.g., according tothe worklist filter and sorting order) which is not currently open andnot locked from view.

If an open study is part of the reading sequence, an “Exit” button oroption in the diagnostic viewer includes a modified icon or other optioncaptioned “Next.” When user presses the “Next” button, the followingoperations are performed independently in parallel. The current study isremoved from the display, and finishing operations begin in thebackground. The study presently stored in a data cache is brought intoview. The next study to be loaded into the cache is determined andbegins loading. Worklist content and an order of studies can be changedat any time due to operations by a current user or other user. Somestudies can be read by other users and thus removed from the worklist.Study or patient information can be changed so the no longer satisfiesone or more worklist criteria, or the study can be deleted.

A current user can modify worklist criteria or change a worklist sortingorder, for example. However, in certain embodiments, for performancereasons, changes to worklist content and/or order are determinedperiodically, and the next study to load is determined based at least inpart on a snapshot of the worklist content. A snapshot of the worklistcontent can be acquired for a certain number of studies (e.g., definedin a system configuration). The snapshot of the worklist content can beupdated when all studies from the current snapshot have been downloaded,for example. Both the currently open study and the cached study arelocked from view, but other studies from the current worklist can beread by other users.

In certain embodiments, the sequence of viewing and loading terminateswhen the user selects a “Finish” option or no studies are left in theworklist. When user selects “Finish,” the current viewer performs doneoperations and closes without bringing up a next loaded study andwithout initiating AutoFetch for the next study or user. The readingsequence at this point is terminated. Already pre-fetched studies can beaccessed through one or more menu or interface options.

A user can switch worklists to look at a different study. Such a studycan be opened regularly with the Done button, for example. A user canexplicitly open a different study from the reading sequence worklist.This study is also provided with a “Next” button, and pressing thebutton behaves in the same way for all currently open studies with“Next” button.

In certain embodiments, a user can work simultaneously with more thanone PACS system on the same client (for example, in teleradiology). Insuch systems, going to the Next study indicates going to the next studythat has been pre-loaded from the same system as the current study.

When more than one diagnostic viewer downloads studies, the viewersnegotiate loading priorities so that only one study is downloaded from aPACS server at any particular time. Decompression of the images not infocus is performed during idle cycles of the client workstationprocessor.

The steps of the improved diagnostic reading workflow are given above asan example only and certain embodiments of the present invention coverother possible combinations of these steps, their subset or combinationof these and other work-steps.

As a further example, if a user has an AutoFetch privilege, AutoFetch onand off items are added to, for example, a right-click menu on a studylist worklist to enable and disable AutoFetch for the worklist. WhenAutoFetch is turned on the worklist is designated as an AutoFetchworklist. When the worklist is designated as an AutoFetch worklist, anAutoFetch enabled icon or identifier can be displayed in conjunctionwith the worklist name, for example. When AutoFetch off is selected fora worklist, the designation of the worklist as an AutoFetch worklist isremoved. In certain embodiments, AutoFetch can be enabled on anyworklist except search results.

When a user selects to open one or more studies on a worklist that isdesignated as an AutoFetch worklist, if no worklists have activeAutoFetch, AutoFetch is activated for the selected worklist and one ormore studies are opened as described further below. IF the worklistalready has an AutoFetch active, the one or more studies are opened asdescribed below. If another worklist already has AutoFetch active, theselected study is opened without AutoFetch.

When a user opens a study with activation of AutoFetch on a worklist,the study opens in the diagnostic viewer. At substantially the sametime, in the background, N (e.g., specified by batch size and/or otherpreferences) viewers are opened with the first studies from the worklistthat are not locked from viewing. AutoFetch is set to active. Theseviewers are opened with AutoFetch active and are loaded in thebackground with an index 1 to N based on their order in the worklist. Ifmore than one study is selected for opening from an AutoFetch activeworklist, the first selected study is opened in the foreground and theothers are opened in the background. If a user has turned off ordisabled opening multiple studies as an AutoFetch batch process, anadditional N viewers are opened with the studies not locked fromviewing.

If a user opens a study when AutoFetch is already active for a worklist,the study is opened in the diagnostic viewer. If more than one study isselected for opening, the first study is opened in the foreground withAutoFetch and the others are opened in the background with AutoFetch.

If a user selects one or more prior exams to be opened, if AutoFetch isactive and a viewer is launched in the background, the viewer isinformed of a maximum number of priors to be fetched along with thecurrent study to be viewed.

If a user requests an identification of the next study, the PACS serverresponds with an identification of the next study that is not lockedfrom view by this or another user from the beginning of the worklistwith an active AutoFetch. In certain embodiments, STAT studies, ifpresent, are considered equally with other studies on the same worklist,for example. If a user changes a sorting order on the worklist, thechange is not reflected in the selection of a next study immediately,but rather with a delay that is determined by the number of studiesspecified by an AutoFetch snapshot size system configuration. A state ofthe worklist is updated when all studies from the snapshot have beenloaded.

If a user selects to deactivate AutoFetch, the study list acceptscommunication from the diagnostic viewer indicating that the userdecided to stop AutoFetch and performs the same actions as if AutoFetchoff had been selected on the worklist menu. If a worklist with an activeAutoFetch becomes empty, AutoFetch can automatically deactivate, forexample. When AutoFetch is deactivated, an AutoFetch indicatorassociated with the worklist can be removed.

Fetching studies in a worklist with AutoFetch can be accomplished asfollows. Studies can be fetched in the background while another studyand/or other information are displayed. When a diagnostic viewer islaunched with a background switch or indicator, the viewer is minimizedand/or is not displayed on the screen. In a Microsoft Windows® task barand/or other application indicator, an icon or indicator for the viewercan display a percentage of study download completed, for example. When100% is reached, the name of the viewer/study can be displayed. Theviewer can begin downloading a specified study (and a specified numberof priors) after the viewer in focus on the display and other viewers infront of the viewer in the fetching queue have completed downloading.After the study and a necessary number of priors, if applicable, areloaded, the viewer remains in the background until it is broughton-screen. The viewer also signals to other viewers that the next viewerin the queue can begin downloading. If a particular study has less thana maximum number of priors specified, only available priors are loaded.If a study has more than a maximum number of priors, only the maximumnumber are loaded. Studies being downloaded in the background are lockedfrom view. If there are multiple viewers loading studies, the viewerscoordinate among themselves so that only a viewer that has focusdownloads until completed, and other viewers download afterwards. Asequence between off-focus or background viewers is such that off-focusviewers download before background viewers, and, among off-focusviewers, the viewers download according to a sequence of theirlaunching.

Studies loaded with AutoFetch can be navigated according to a pluralityof interface options. When a diagnostic viewer is launched withAutoFetch, a Next button shall appear alone or in conjunction withDone/Finish button options. Selecting “Next” is this mode closes thestudy as the Done option would do in a non-AutoFetch mode and bring intofocus the next viewer from the viewers in the background that has thelowest queue index. Selecting Next also generates a request foridentification of the next study from the server and launches a nextinstance of the diagnostic viewer with AutoFetch and background loadingoptions selected. The next study and a specified number of priors (ifany) will be loaded in the background. Selecting Done rather than Nextwill close the current study without bringing any background viewers upfor display or requesting the next study. Selecting Finish closes thestudy and indicates to the study list that the AutoFetch for thisworklist should be deactivated. Additionally, selection of Finishcommunicates to other viewers that their Next buttons/options will bereverted back to the regular Done button/option. The Done button withthe functionality described above can be placed on a patient folder, forexample.

When studies are loaded from more than one distinct server with anactive AutoFetch, navigation is performed between studies loaded fromthe same server. In certain embodiments with large installation andbusiness continuity configurations, studies coming from different nodesare not treated as coming from different servers/systems.

In certain embodiments, a variety of user preferences can be set. Forexample, an AutoFetch batch size preference specifying a number ofstudies that are pre-loaded when AutoFetch is activated. If batch sizeis set to zero (0) studies, no study loading is performed. If batch sizeis N>0 studies, then after the first study is opened, N next studiesfrom the batch are downloaded into a local cache. N studies aremaintained in the local cache. If a batch size is not specified, thesize will be treated as zero (a default value).

An AutoFetch priors preference includes a numeric value specifying anumber of prior studies to be auto-fetched along with the current studywhen AutoFetch mode is active. If AutoFetch priors is set to zerostudies, then no priors are pre-fetched. If AutoFetch priors is M>0studies, then a maximum of M latest priors are fetched along with thecurrent study. If AutoFetch priors is not specified, then a default ofzero is applied.

An open multiple studies as AutoFetch batch preference is a Booleanvalue (e.g., represented by a checkbox) that specifies whether openingmultiple studies by a user on an AutoFetch worklist is treated ascreation of an initial batch. If this preference is set to off, anadditional N studies are included in a pre-loading batch when multiplestudies are open. If this preference is set to on, the studies selectedby the user are considered the pre-loading batch. By default, thispreference is set to on.

In certain embodiments, an AutoFetch privilege can also be specified todetermine whether a user can control AutoFetch functionality.

In certain embodiments, an AutoFetch snapshot size determines a numberof studies that are to be included in a snapshot of the AutoFetchworklist.

In addition to information described above defining the workflowassociated with the worklists and handling the data transfer between theserver and the local workstation, embodiments can also includeadditional steps for data handling, grooming, and/or pre-processing bythe viewers opened in silent or background mode in anticipation of theiractivation in the course of diagnostic reading. Operations include butare not limited to data processing (e.g., sharpening/smoothing/edgedetection, etc.), multi-planar image reconstruction, computer-aideddiagnostics based on digital data processing, image registration and/orfusion, image arrangement, requesting additional images and/or relatedmedical data from various data repositories, etc.

Thus, use of a loading plan in conjunction with pre-loading and/or imageslice/compression algorithms can help provide a reduction in latencytime to open a new exam study.

In certain embodiments, the loading plan can incorporate specialprovisions to minimize or reduce the time for showing of the first imagein a study by parsing the data and metadata for the image up to somesubset of the data/metadata that is sufficient to start the workflow.The loading plan can include auxiliary objects not included in the studythat are displayed on a user's screen to reduce latency time (e.g., anoverview image, a static image, a coarse quality image, etc.).

Certain embodiments can be applied beyond clinical environments to avariety of information systems that support workflows (e.g., air trafficcontrol, shipping systems to track packages, customers, nodes,transportation, etc.). Certain embodiments provide a system that managesretrieval, transportation, and delivery of components. For every stageof the workflow, a certain subset of the objects are needed. The objects(e.g., pieces of information or plywood or concrete) can be stored invarious places. The loading plan and a graph of the objects needed atvarious stages of the workflow can be provided and used. The graphpoints to different objects, including nested and/or linked objects,involved in the workflow. One object may not care about a context of theother object, and the loading plan can follow pointers or links from oneobject to the next.

For example, a diagnostic viewer is directed to retrieve images for aradiologist user. The viewer does not already know what images areinvolved but can access a descriptive file which indicates the imagesinvolved and indicates that a first series is a consolidated series withthick resolution slices with a high resolution difference storedelsewhere, for example. As an example, the viewer only needs theconsolidated series for a first displayed series but needs highresolution images for a third displayed series. Objects or images forviewing can be loading using a loading plan for objects and a loadinggraph including a knowledge of the location(s) of the objects and howthe objects can be delivered. The loading plan includes informationdescribing image and information layout for the viewer.

The loading plan for the data is used in conjunction with a plurality ofdata delivery nodes that are notified that they are to deliver thespecified data objects. Each node can have loading plans for variouscustomers and the nodes balance the load according to the variousloading plans. As an example, different nodes should know aboutbottlenecks ahead of them and should not use all resources for one userbecause that user's computer has a processor with low processing powerand, even if all requested images are delivered to that user's computer,the user will still be waiting for the images to be decompressed.

Thus, for display of images via a diagnostic viewer and/or other taskinvolving objects for retrieval and use, there is a graph of objectsneeded for each step and a loading plan to load those objects. Theloading plan is delivered to all nodes needed to carry those objects.Each node/broker is a transportation agent and has a loading plancombined from the loading plans of all of its clients. When eachtransportation broker multi-threads delivery of various objects tovarious clients, the broker balances demands of the clients taking intoaccount further nodes and further bottlenecks that can occur down thedelivery chain. The work/loading plan can also change. For example, asystem is loading images one by one but launching of a third partyapplication involves using all available images at once, so the loadingplan is changed to accommodate loading of all images together.

FIG. 5 illustrates a flow diagram for a method 500 for transferringimages for display at a client workstation in accordance with anembodiment of the present invention. At 510, a data list is createddescribing data types and data objects to be delivered to implement animaging workflow. In certain embodiments, the data list can berepresented as a graph or other structured representation of resources,for example.

At 520, one or more image loading plans are established to specify arecommended priority or order for delivery of objects referred to in thedata list. The loading plan includes a description of image readingworkflows including data types and data objects for executing of thereading workflow. The description can also include a technical mechanismfor retrieval and delivery of particular data objects to a readingapplication for a reading workflow. The loading plan can also include,for example, a description of which data should be available to aviewing workstation application at one or more given stages of thereading workflow. Delivery engines/nodes and other hardware/software canbe arranged in a delivery chain to provide delivery of data from storageto a viewing workstation in accordance with the loading plan.

At 530, a node or engine loading plan can be generated for each deliverynode/engine based on the general loading plan. The node/engine loadingplan serves as an operational algorithm for a particular deliverynode/engine. The loading plan(s) include one or more priorities forhandling of resources involved in image display.

At 540, the general loading plan and/or node/engine loading plans arereconciled. For example, loading plans can be coordinated for aplurality of delivery nodes/engines to reduce data congestion andbottlenecks along the delivery chain. A priority, order, and/or speed ofdata retrieval, transfer, and/or processing by delivery nodes/enginescan be changed in response to an updated node/engine loading planresulting from multiple loading plan conflict, resource availability,and/or user input, for example. Intermediate engines (e.g., services,data storage, etc.) can be synchronized using loading plan(s) to helpavoid bottlenecks, for example.

At 550, data is concurrently delivered by delivery engines/nodes for oneor more independent workflows. Data delivery can be facilitated usingshared resources according to the loading plan(s). Load balancing ofparallel delivery engines/nodes can be performed for distribution ofshared system resources between independent workflows. Data can bedelivered using one or more compression strategies, data types, etc., inconjunction with the loading plan(s) and data list, for example. Aspecial start up of initial format can be implemented to display someinitial information to a user while loading additional image data in thebackground for replacement on the display. A time for showing of a firstimage can be reduced by parsing the data for the image and relatedmetadata up to a subset that is sufficient to start the image displayworkflow.

As an example, the next viewing application can be preloaded in thebackground, and the viewing application can initiate a study openingworkflow in the background. When a reviewing physician finishes readingthe first study, he or she automatically goes to the next view frombackground to foreground. The next view is then loaded and ready withtools, hanging protocol, and related prior images (if applicable)configured and ready for view, for example.

One or more of the steps of the method 500 may be implemented alone orin combination in hardware, firmware, and/or as a set of instructions insoftware, for example. Certain examples may be provided as a set ofinstructions residing on a computer-readable medium, such as a memory,hard disk, DVD, or CD, for execution on a general purpose computer orother processing device.

Certain examples may omit one or more of these steps and/or perform thesteps in a different order than the order listed. For example, somesteps may not be performed in certain examples. As a further example,certain steps may be performed in a different temporal order, includingsimultaneously, than listed above.

Thus, certain embodiments provide for creation and use of one or moreloading plans for delivery of image data for viewing. A loading plan caninclude auxiliary objects not included in an image study that aredisplayed on a user's screen initially to reduce effective latency timefor study display. Loading plans can be applied to a variety ofinformation systems that support workflows (e.g., air traffic control,shipping systems to track packages, customers, nodes, transportation,etc.). Certain embodiments provide systems and methods to manageretrieval, transportation, and delivery of data objects to be combinedfor display and/or interaction by a user. For each stage of a workflow,a certain subset of the objects is utilized. The objects (e.g., piecesof information or materials) can be stored in various places. For aworklist, the loading plan is used in conjunction with a list or graphof the objects for various stages of the workflow. The graph points todifferent objects and can be nesting or linked graph/list, for example.One object may not care about the context of another object, and theloading plan can follow pointers in the graph to identify the relevantobject(s).

For example, a viewer requests images for display. The viewer does nothave a complete picture of the images involved but accesses adescriptive file that indicates the images are series one, two, andthree. Image series one is a consolidated series with thick resolutionslices and high resolution difference information stored at anotherlocation. Only consolidated images are used for series 1 in the displayrequest, but high resolution images are used for series three. A loadingplan and loading graph are generated with knowledge of the location ofthe image series objects and how the objects can be delivered. Theloading plan includes the desired image layout for display. The loadingplan for the data is relayed to several nodes in the delivery chain tonotify the nodes that the nodes are to deliver certain objects. Eachnode may have loading plans for various customers and balances the loadbetween the plans. Different nodes are informed of bottlenecks ahead ofthem and adaptively determine resource usage for one or more users basedon resource availability and congestion in this and surrounding nodes.

Thus a node serves as a transportation agent or broker with a loadingplan combined from loading plans of all of its clients. When eachtransportation broker multithreads delivery of various objects tovarious clients, the broker balances demands of the clients taking intoaccount surrounding nodes and bottlenecks in the delivery chain ofnodes. Additionally, a loading plan can change. For example, a currentrequest involves loading images one at a time but launching of a thirdparty application on the client workstation involves utilizing allavailable images at once, so the loading plan is changed to requestloading of all images together. Thus, status updates can be passed tonodes to allow those nodes to reconsider and possibly alter theirloading plans.

Thus, certain embodiments help improve an efficiency of deliveringinformation to client workstations to reduce latency time and load on aclinical information system, such as a PACS. Users typically request aselected part of available content for initial review. Even if all of astudy's content is available, reading may be delayed waiting foradditional information and/or metadata, such as hanging protocolinformation, prior exam information, etc. For each specific study, usinga loading plan, information involved in the reading process can bealgorithmically identified and retrieved. Some of the information isneeded before action can be taken in the reading workflow, while otherinformation is not involved until later in the reading workflow. A listof resources for the exam/study and a priority of handling theseresources, as well as how the resources should be loaded onto thereading workstation, are provided to intermediate engines (services,data storage, etc.), which are synchronized according to the plan sothat loading, storing, packaging are synchronized and bottlenecks arereduced or avoided. As one example, pre-fetching or pre-loading can beused to assist in loading and prioritizing of images and related datafor display.

For example, “smart” prefetching of a next to be read study from aworklist of a client viewing workstation can be performed according to aloading plan. A physician, for example, reads studies in a predefinedorder coinciding with the worklist ordered according to his/hercriteria. When the first study is retrieved from the worklist uponinitiation of the reading workflow, a certain number of next studies areanticipated and preloaded on the workstation. Rather than preloading acontext and caching the context on the workstation, a next viewingapplication is loaded in the background. A workflow of opening that nextstudy (including hanging protocols, related prior studies forcomparison, etc.) is initiated in the background on the workstation.When the physician finishes reading the first study, rather than goingto the worklist and opening the next study, the physician isautomatically brought to the next view, which goes from background toforeground. The next view is already loaded with tools, a hangingprotocol, and prior images configured and ready for review.

In certain embodiments, no physical location on a client workstationdisk or memory contains sensitive patient information. The viewer usesprotected memory space available to the viewing application for loadingand display. If a power surge or termination of process occurs, nosensitive information is exposed. The protected memory is cleared uponreboot of the computer.

Certain embodiments provide a technical effect of improved diagnosticreading efficiency through reduction of latency time for opening newexams. Images and related data and metadata are pre-loaded into localstorage so that data is more immediately available when the userrequests review of the next exam. Image(s) are transferred to a localmachine so that display and interaction can be faster. A worklist can beconfigured to allow or prohibit local storage, processing, and/orviewing of images and related information.

It should be understood by any experienced in the art that the inventiveelements, inventive paradigms and inventive methods are represented bycertain exemplary embodiments only. However, the actual scope of theinvention and its inventive elements extends far beyond selectedembodiments and should be considered separately in the context of widearena of the development, engineering, vending, service and support ofthe wide variety of information and computerized systems with specialaccent to sophisticated systems of high load and/or high throughputand/or high performance and/or distributed and/or federated and/ormulti-specialty nature.

Certain embodiments contemplate methods, systems and computer programproducts on any machine-readable media to implement functionalitydescribed above. Certain embodiments may be implemented using anexisting computer processor, or by a special purpose computer processorincorporated for this or another purpose or by a hardwired and/orfirmware system, for example.

One or more of the components of the systems and/or steps of the methodsdescribed above may be implemented alone or in combination in hardware,firmware, and/or as a set of instructions in software, for example.Certain embodiments may be provided as a set of instructions residing ona computer-readable medium, such as a memory, hard disk, DVD, or CD, forexecution on a general purpose computer or other processing device.Certain embodiments of the present invention may omit one or more of themethod steps and/or perform the steps in a different order than theorder listed. For example, some steps may not be performed in certainembodiments of the present invention. As a further example, certainsteps may be performed in a different temporal order, includingsimultaneously, than listed above.

Certain embodiments include computer-readable media for carrying orhaving computer-executable instructions or data structures storedthereon. Such computer-readable media may be any available media thatmay be accessed by a general purpose or special purpose computer orother machine with a processor. By way of example, suchcomputer-readable media may comprise RAM, ROM, PROM, EPROM, EEPROM,Flash, CD-ROM or other optical disk storage, magnetic disk storage orother magnetic storage devices, or any other medium which can be used tocarry or store desired program code in the form of computer-executableinstructions or data structures and which can be accessed by a generalpurpose or special purpose computer or other machine with a processor.Combinations of the above are also included within the scope ofcomputer-readable media. Computer-executable instructions comprise, forexample, instructions and data which cause a general purpose computer,special purpose computer, or special purpose processing machines toperform a certain function or group of functions.

Generally, computer-executable instructions include routines, programs,objects, components, data structures, etc., that perform particulartasks or implement particular abstract data types. Computer-executableinstructions, associated data structures, and program modules representexamples of program code for executing steps of certain methods andsystems disclosed herein. The particular sequence of such executableinstructions or associated data structures represent examples ofcorresponding acts for implementing the functions described in suchsteps.

Embodiments of the present invention may be practiced in a networkedenvironment using logical connections to one or more remote computershaving processors. Logical connections may include a local area network(LAN) and a wide area network (WAN) that are presented here by way ofexample and not limitation. Such networking environments are commonplacein office-wide or enterprise-wide computer networks, intranets and theInternet and may use a wide variety of different communicationprotocols. Those skilled in the art will appreciate that such networkcomputing environments will typically encompass many types of computersystem configurations, including personal computers, hand-held devices,multi-processor systems, microprocessor-based or programmable consumerelectronics, network PCs, minicomputers, mainframe computers, and thelike. Embodiments of the invention may also be practiced in distributedcomputing environments where tasks are performed by local and remoteprocessing devices that are linked (either by hardwired links, wirelesslinks, or by a combination of hardwired or wireless links) through acommunications network. In a distributed computing environment, programmodules may be located in both local and remote memory storage devices.

An exemplary system for implementing the overall system or portions ofembodiments of the invention might include a general purpose computingdevice in the form of a computer, including a processing unit, a systemmemory, and a system bus that couples various system componentsincluding the system memory to the processing unit. The system memorymay include read only memory (ROM) and random access memory (RAM). Thecomputer may also include a magnetic hard disk drive for reading fromand writing to a magnetic hard disk, a magnetic disk drive for readingfrom or writing to a removable magnetic disk, and an optical disk drivefor reading from or writing to a removable optical disk such as a CD ROMor other optical media. The drives and their associatedcomputer-readable media provide nonvolatile storage ofcomputer-executable instructions, data structures, program modules andother data for the computer.

While the invention has been described with reference to certainembodiments, it will be understood by those skilled in the art thatvarious changes may be made and equivalents may be substituted withoutdeparting from the scope of the invention. In addition, manymodifications may be made to adapt a particular situation or material tothe teachings of the invention without departing from its scope.Therefore, it is intended that the invention not be limited to theparticular embodiment disclosed, but that the invention will include allembodiments falling within the scope of the appended claims.

1. A method for transferring image data via a delivery chain for displayat a client workstation, said method comprising: creating a data listdescribing image data to be delivered to implement an imaging workflow;establishing a general loading plan to specify a recommended priorityfor delivery of the image data in the data list; generating a nodeloading plan for each node in the delivery chain based on the generalloading plan; reconciling at least one of the general loading plan andthe node loading plan; and delivering the image data via the nodes ofthe delivery chain based on the general loading plan, the node loadingplan for each node in the delivery chain, and the data list.
 2. Themethod of claim 1, wherein the data list is represented as a graph ofresources.
 3. The method of claim 1, wherein a node in the deliverychain includes a plurality of node loading plans for a plurality ofimage data delivery workflows.
 4. The method of claim 1, wherein thegeneral loading plan includes a description of 1) data involved and 2)an appropriate retrieval and delivery mechanism for each stage of aworkflow.
 5. The method of claim 1, wherein reconciling furthercomprises coordinating loading plans for a plurality of delivery nodesto reduce data congestion and bottleneck along the delivery chain. 6.The method of claim 1, wherein reconciling further comprises changing atleast one of priority, order, data retrieval speed, data transfer speed,and data processing by nodes in the delivery chain in response to anupdated node loading plan resulting from at least one of loading planconflict and resource availability.
 7. The method of claim 1, whereindelivering further comprises concurrently delivering image data by nodesin the delivery chain for a plurality of independent workflows.
 8. Themethod of claim 1, further comprising employing a compression strategywith respect to the image data for delivery of the image data inconjunction with the general loading plan, the node loading plan foreach node in the delivery chain, and the data list.
 9. The method ofclaim 1, further comprising displaying initial information for a userwhile delivering the image data in a background of the clientworkstation processing.
 10. The method of claim 1, further comprisingpre-loading a next viewing application with next image data in thebackground while the image data delivered is viewed on the clientworkstation.
 11. The method of claim 10, wherein the pre-loadingincludes loading the next image data with tools, a hanging protocol, andapplicable prior images configured and ready for viewing at the clientworkstation.
 12. A picture archiving and communication system, saidsystem comprising: a delivery chain including a plurality of nodesretrieving image data from storage and transmitting the image data froma server to a workstation for display; a processor and associated memoryincluding a data list and a general loading plan, the data listdescribing image data to be delivered to implement an imaging workflowand the general loading plan to specify a recommended priority fordelivery of the image data in the data list, the processor providing anode loading plan to each node in the delivery chain based on thegeneral loading plan, wherein the delivery chain operates with the datalist, general loading plan, and each node loading plan to deliverrequested image data via the delivery chain.
 13. The system of claim 12,wherein the data list is represented as a graph of resources.
 14. Thesystem of claim 12, wherein a node in the delivery chain includes aplurality of node loading plans for a plurality of image data deliveryworkflows.
 15. The system of claim 12, wherein the general loading planincludes a description of 1) data involved and 2) an appropriateretrieval and delivery mechanism for each stage of a workflow.
 16. Thesystem of claim 12, wherein the processor and the delivery chaincoordinate node loading plans for a plurality of delivery nodes toreduce data congestion and bottleneck along the delivery chain.
 17. Thesystem of claim 12, wherein the processor adjusts at least one ofpriority, order, data retrieval speed, data transfer speed, and dataprocessing by nodes in the delivery chain in response to an updated nodeloading plan resulting from at least one of loading plan conflict andresource availability.
 18. The system of claim 12, wherein nodes in thedelivery chain concurrently deliver for a plurality of independentworkflows based on a plurality of node loading plans.
 19. The system ofclaim 12, wherein the processor and the delivery chain employ acompression strategy with respect to the image data for delivery of theimage data in conjunction with the general loading plan, the nodeloading plan for each node in the delivery chain, and the data list. 20.The system of claim 12, further comprising displaying initialinformation for a user while delivering the image data in backgroundprocessing of the workstation.
 21. The system of claim 12, wherein theprocessor pre-loads a next viewing application with next image data inthe background at the workstation while the image data delivered isviewed on the workstation.
 22. The system of claim 21, wherein thepre-loading includes loading the next image data with tools, a hangingprotocol, and applicable prior images configured and ready for viewingat the workstation.
 23. The system of claim 12, wherein the processorresides on at least one of a picture archiving and communications serverand the workstation, and wherein the delivery chain resides on thepicture archiving and communications server and a network connecting theserver with the workstation.
 24. A computer readable medium having a setof instructions for execution on a computing device, the set ofinstructions executing a method for transferring image data via adelivery chain for display at a client workstation, the methodcomprising: creating a data list describing image data to be deliveredto implement an imaging workflow; establishing a general loading plan tospecify a recommended priority for delivery of the image data in thedata list; generating a node loading plan for each node in the deliverychain based on the general loading plan; reconciling at least one of thegeneral loading plan and the node loading plan; and delivering the imagedata via the nodes of the delivery chain based on the general loadingplan, the node loading plan for each node in the delivery chain, and thedata list.